Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta).

Jd, Smith; Ac, Zakrzewski; Jj, Johnston; Jl, Roeder; Boomer, Joseph; Fg, Ashby; Ba, Church

doi:10.1037/xan0000071

Cited by 16 publications

(31 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specifically, both tasks used unframed pixel box stimuli with identical size and pixel density levels described below in Stimuli. However, in Smith et al (2015), Murph's stimuli were green (in his RB task) and light red (in his II task). Here, Murph's stimuli were light blue (in his RB task) and yellow (in his II task).In Smith et al (2015), Murph began with an RBv task in which the relevant dimension was size (X-axis).…”

Section: Methodsmentioning

confidence: 99%

“…Like before, the A and B ellipses were switched and rotated to a 45-degree angle. However, unlike the IIM task in Smith et al (2015), during IIm training here, 100% of trials sampled stimuli from the upper half of the X-dimension (size) and lower half of the Y-dimension (density). At transfer, 10% of all trials were sampled from the top half of the Y-dimension (density) and bottom half of the X-dimension (size).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

Zakrzewski¹,

Church²,

Smith³

2018

Journal of Comparative Psychology

Self Cite

View full text Add to dashboard Cite

Cognitive psychologists distinguish implicit, procedural category learning (stimulus-response associations learned outside declarative cognition) from explicit-declarative category learning (conscious category rules). These systems are dissociated by category learning tasks with either a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. In the present experiments, humans and two monkeys learned II and RB category tasks fostering implicit and explicit learning, respectively. Then they received occasional transfer trials-never directly reinforced-drawn from untrained regions of the stimulus space. We hypothesized that implicit-procedural category learning-allied to associative learning-would transfer weakly because it is yoked to the training stimuli. This result was confirmed for humans and monkeys. We hypothesized that explicit category learning-allied to abstract category rules-would transfer robustly. This result was confirmed only for humans. That is, humans displayed explicit category knowledge that transferred flawlessly. Monkeys did not. This result illuminates the distinctive abstractness, stimulus independence, and representational portability of humans' explicit category rules. (PsycINFO Database Record

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

Zakrzewski¹,

Church²,

Smith³

2018

Journal of Comparative Psychology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although we know of no theory that offers an answer to this question, one possibility is that different types of information are automatized in RB and II tasks. For example, the evidence is good that initial II learning is of SR associations, whereas initial learning in RB tasks is of abstract rules (Ashby & Waldron, 1999; Casale, Roeder, & Ashby, 2012; Smith et al, 2015). These data suggest that one plausible hypothesis is that SR associations are automatized in II tasks, whereas the rule is automatized in RB tasks.…”

Section: Introductionmentioning

confidence: 99%

What is automatized during perceptual categorization?

Roeder

Ashby

2016

Cognition

Self Cite

View full text Add to dashboard Cite

An experiment is described that tested whether stimulus-response associations or an abstract rule are automatized during extensive practice at perceptual categorization. Twenty-seven participants each completed 12,300 trials of perceptual categorization, either on rule-based (RB) categories that could be learned explicitly or information-integration (II) categories that required procedural learning. Each participant practiced predominantly on a primary category structure, but every third session they switched to a secondary structure that used the same stimuli and responses. Half the stimuli retained their same response on the primary and secondary categories (the congruent stimuli) and half switched responses (the incongruent stimuli). Several results stood out. First, performance on the primary categories met the standard criteria of automaticity by the end of training. Second, for the primary categories in the RB condition, accuracy and response time (RT) were identical on congruent and incongruent stimuli. In contrast, for the primary II categories, accuracy was higher and RT was lower for congruent than for incongruent stimuli. These results are consistent with the hypothesis that rules are automatized in RB tasks, whereas stimulus-response associations are automatized in II tasks. A cognitive neuroscience theory is proposed that accounts for these results.

show abstract

“…Zakrzewski and her colleagues have begun research to explore these issues (e.g., [ 68 ]). She asks whether RB and II category knowledge are qualitatively different in cognitive content, and whether they are different in the same way for humans and macaques.…”

Section: Category Rules and Representational Portabilitymentioning

confidence: 99%

“…Figure 16 shows our experimental situation [ 68 ]. We broke the category structures generally used in RB-II research ( Figure 12 ) into training and transfer distributions.…”

Section: Category Rules and Representational Portabilitymentioning

confidence: 99%

Categorization: The View from Animal Cognition

Smith

Zakrzewski

Johnson

et al. 2016

Behavioral Sciences

View full text Add to dashboard Cite

Exemplar, prototype, and rule theory have organized much of the enormous literature on categorization. From this theoretical foundation have arisen the two primary debates in the literature—the prototype-exemplar debate and the single system-multiple systems debate. We review these theories and debates. Then, we examine the contribution that animal-cognition studies have made to them. Animals have been crucial behavioral ambassadors to the literature on categorization. They reveal the roots of human categorization, the basic assumptions of vertebrates entering category tasks, the surprising weakness of exemplar memory as a category-learning strategy. They show that a unitary exemplar theory of categorization is insufficient to explain human and animal categorization. They show that a multiple-systems theoretical account—encompassing exemplars, prototypes, and rules—will be required for a complete explanation. They show the value of a fitness perspective in understanding categorization, and the value of giving categorization an evolutionary depth and phylogenetic breadth. They raise important questions about the internal similarity structure of natural kinds and categories. They demonstrate strong continuities with humans in categorization, but discontinuities, too. Categorization’s great debates are resolving themselves, and to these resolutions animals have made crucial contributions.

show abstract

Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta).

Cited by 16 publications

References 71 publications

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

What is automatized during perceptual categorization?

Categorization: The View from Animal Cognition

Contact Info

Product

Resources

About